Published date Posted on Indeed on May 12, 2022 (15 d ago)


  • Develop, create, maintain, manage, and optimize data pipelines as workloads move from development to production for specific use cases.
  • Responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
  • Assist with renovating the data management infrastructure to drive automation in data integration and management.
  • Develop algorithms and predictive models to solve critical business problems.
  • Develop tools and libraries that will help analytics team members more efficiently interface with huge amounts of data.
  • Analyze large, noisy datasets and identify meaningful patterns that provide actionable results.
  • Develop and automate new enhanced imputation algorithms.
  • Work with data lakes and databases including any aspect of administration or support required to maintain them

TECHNICAL COMPETENCIES (Knowledge, Skills & Abilities)

  • Excellent at solving analytical problems using quantitative approaches.
  • Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
  • Fluency with at least one scripting language such as Phyton and other languages like R, Java, C, C++, C# is a plus
  • Strong knowledge of DevOps workflow, cloud-native platforms (containers, Kubernetes, serverless, etc.) and tools (such as Git), and infrastructure as code (IaC) tools (such as CloudFormation or Terraform)
  • Strong ability to collaborate with a variety of roles and harmonize the relationship between business and IT.
  • Strong passion for empirical research and for answering hard questions with data.
  • Flexible analytic approach that allows for results at varying levels of precision..
  • Highly self-motivated and directed.
  • Keen attention to detail.
  • Ability to effectively prioritize and execute tasks in a high-pressure environment


  • Bachelors degree in computer science, mathematics, or statistics
  • Minimum 8 years equivalent IT work experience and 5 years in Data Engineering
  • Minimum 2 years of cloud platform experience
  • Experience in AI Hardware in managing and troubleshooting distributed systems like
  • Apache Hadoop, spark and familiarity with Public cloud IaaS/PaaS
  • Familiar with common techniques and general ML programming to ensure quality of algorithms before pushing them to production
  • Experience with BI and Reporting Tools
  • Experience with Data Integration tools like Spark/Databricks or equivalent
  • Experience in Linux/Unix shell scripting

Job Type: Full-time

Pay: $155,000.00 - $160,000.00 per year


  • 401(k)
  • Dental insurance
  • Flexible spending account
  • Health insurance
  • Health savings account
  • Paid time off
  • Parental leave
  • Professional development assistance
  • Retirement plan
  • Vision insurance


  • 8 hour shift
  • Monday to Friday

Supplemental Pay:

  • Signing bonus


  • Data Engineering: 8 years (Required)
  • Cloud: 2 years (Required)
  • Python: 5 years (Required)

Work Location: Remote

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